Building a generative AI data assistant for a Fortune 500 company

Our direct client was a Big Three consulting firm working for a Fortune 500 food multinational whose brands are sold in more than 150 countries. The consultancy led the strategy and senior client relationship; Tailor Hub brought the AI engineering expertise and production capability needed to turn the initiative into a working system.

Business users depended on analysts to answer routine questions, while the Data team spent part of its time translating those requests into queries and reports. The company wanted an assistant that could answer questions over structured data and documents in plain language, with enough accuracy to support real decisions.

In 2024, the architectures and roles around generative AI were still taking shape. The client's Data function knew the systems and underlying information, but this initiative required a senior AI engineering profile capable of turning an emerging use case into a technical plan and guiding its implementation.

One of Tailor Hub's most experienced generative AI engineers defined the architecture and established how the existing systems and teams would participate in the build.

The system connected the client's APIs and data services to large language models. Non-technical users could ask questions and receive answers supported by tables and charts when the data required context. Next.js covered the frontend and backend, while AWS Bedrock kept model access within the client's existing cloud governance.

Two more Tailor engineers joined the implementation, working alongside the client's Data team. Tailor set the technical direction and built the critical AI layer; the internal team contributed its knowledge of the systems and information.

In 2026, the end client returned to the team that had defined the original system to design and build its next agentic phases.